AI Search Citation Factors for Local Health Practices

This paper examines the factors that determine whether an independent local health practice appears in AI-generated recommendation responses across ChatGPT, Claude and Gemini. Drawing on a dataset of 216 New Jersey health practices tested using standardized local search prompts, we identify the entity visibility gap as the primary barrier to AI citation for local businesses. We synthesize findings from existing literature on AI citation factors - including brand mention volume, content freshness, structured format, and schema markup - and apply them to the local health vertical. Our dataset reveals that 98% of practices scored zero across all three AI models, with no practice achieving cross-model visibility. We conclude that a single well-indexed third-party publication placement may be sufficient to generate initial AI citation presence, and that local health practices represent the most underserved segment of the AI visibility market.